Distribution modelling of Ningaloo mesophotic (deepreef) communities

Joe TurnerSupervisors: Gary Kendrick, Renae Hovey, Russ Babcock

Ningaloo Outlook –A partnership between BHP and CSIRO

WESTERN COASTAL/OCEAN & ATMOSPHERE

Ningaloo Outlook is a BHP-CSIRO Industry-Science Marine Research Partnership investing A$5.4 million over five years to gather new knowledge on the Ningaloo reef and its important ecological values

• Occur from 30 m to bottom of the photic zone (up to 150 m). • Initially suggested as a refuge (Bongaerts et al., 2010).

• Can harbor distinct communities (Rocha et al., 2018).

Background: Mesophotic Ecosystems

Shallow ReefsCoral dominated

Upper MesophoticFewer corals, transition to deeper specialised species.

Lower MesophoticNon-photosynthetic communities.

• Distribution models identify relationshipsbetween a species and environmentalfactors.

• Uses niche theory.

• Fundamental niche: Environmentalconditions where a species will persist.

• Realised niche: The space inhabitedfollowing competitive interactions.

Background: Distribution Modelling

Study Area: Ningaloo

• Multibeam Echo Sounders• Bathymetry – Depth• Backscatter – Hardness

• This data is then used to create Digital Elevation Models (DEMs) of the seafloor.

• Use ArcGIS to compute topographical derivatives e.g. slope, aspect, rugosity.

Methods: Acoustics

https://www.bas.ac.uk/wp-content/uploads/2015/07/SWATH-illustration_FINAL-e1436863385756.jpg

• Acoustic data does not provide a direct observation of the seabed.

• Need to use visual methods to confirm what is there.

• Towed Video

• Starbug AUV

Methods: Ground Truthing

Methods: Modelling Techniques

• Uses statistical techniques so that computers “learn” from the input data to identify patterns and make predictions.

• Video/AUV points = Training data.

• Three taxonomic groups:• Corals• Macroalgae• Sponges

• Each point has associated values with the predictor variables e.g. depth. https://imgs.xkcd.com/comics/machine_learning.png

Methods: Modelling Techniques• Six modelling methods used:

• Simple: Classification Trees, MARS, Generalised Linear Models.• Complex: Random Forest, Boosted Regression Trees, MaxEnt.• Ensemble.

• Change grid size used:• 10 m; 50 m; 100 m; 250 m

• Subset data:• 5-Fold cross-validation, 10 replicates.• Validation data: Osprey Bay (Southernmost area).

Test dataTraining data

• Power of a model to represent the world as measured against reality.

• Sensitivity (true positive rate): proportion of positives that are correctly identified.

• Specificity (true negative rate): proportion of negatives that are correctly identified

• True skill statistic (TSS)• Sensitivity + Specificity – 1

• Area under receiver operating characteristics curve (AUC)

Methods: Map/Model Accuracy

Results: Model Resolution

Results: Model Resolution

Results: Model Resolution

Results: Model Resolution

10 m 50 m

100 m 250 m

• Corals:• Fine-scale best• Narrow niche

• Macroalgae and Sponges:• Larger grid sizes best• Broad groups = diversity of niches

• Ensemble methods extremely useful

Summary

OCEAN & ATMOSPHERE

Twitter: @Joseph_A_Turner

Email: joseph.turner@research.uwa.edu.au

Acknowledgements:

BHP-CSIRO Ningaloo Outlook Marine Research Partnership

Supervisors: Gary Kendrick, Russ Babcock, and Renae Hovey

Deep Reefs Fieldwork Team: Karl Forcey, Nick Mortimer, Matt Boyd, Ryan Crossing, Rob Gregor